IBMDeveloperMEA/YPDL-Build-a-movie-recommendation-engine-with-TensorFlow
In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.
This project helps anyone in the entertainment or e-commerce industries to build a system that suggests movies to users. You input existing movie ratings from users, and it outputs personalized movie recommendations. This is ideal for product managers or data scientists building user-centric recommendation features for streaming platforms or online stores.
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Use this if you need to create a movie recommendation system that learns from past user ratings to suggest new movies a user might like.
Not ideal if you need to recommend items other than movies, or if you prefer not to use a Restricted Boltzmann Machine approach for recommendations.
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May 10, 2022
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